RESEARCH ARTICLE
Within-Site Variation in Feather Stable
Hydrogen Isotope (δ2Hf) Values of Boreal
Songbirds: Implications for Assignment to
Molt Origin
Cameron J. Nordell1☯, Samuel Haché1,2☯*, Erin M. Bayne1, Péter Sólymos1, Kenneth
R. Foster3, Christine M. Godwin3, Richard Krikun4, Peter Pyle5, Keith A. Hobson6,7
a11111
1 Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada, 2 Environment and
Climate Change Canada, Yellowknife, Northwest Territories, Canada, 3 Owl Moon Environmental Inc., Fort
McMurray, Alberta, Canada, 4 Lesser Slave Lake Bird Observatory, Slave Lake, Alberta, Canada,
5 Institute for Bird Populations, Point Reyes Station, California, United States of America, 6 Environment
and Climate Change Canada, Saskatoon, Saskatchewan, Canada, 7 Department of Biology, University of
Western Ontario, London, Ontario, Canada
☯ These authors contributed equally to this work.
* [email protected]
OPEN ACCESS
Citation: Nordell CJ, Haché S, Bayne EM, Sólymos
P, Foster KR, Godwin CM, et al. (2016) Within-Site
Variation in Feather Stable Hydrogen Isotope (δ2Hf)
Values of Boreal Songbirds: Implications for
Assignment to Molt Origin. PLoS ONE 11(11):
e0163957. doi:10.1371/journal.pone.0163957
Editor: Yan Ropert-Coudert, Centre National de la
Recherche Scientifique, FRANCE
Received: May 14, 2016
Accepted: September 16, 2016
Published: November 2, 2016
Copyright: © 2016 Nordell et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: Data are available
from the figshare repository at the following DOI:
10.6084/m9.figshare.4059615
Funding: Owl Moon Environmental Inc. supported
the salaries of K.F and C.G., but did not have any
additional role in the study design, data collection
and analysis, decision to publish, or preparation of
the manuscript. The specific roles of these authors
are articulated in the ‘author contributions’ section.
Competing Interests: The commercial affiliation
with Owl Moon Environmental Inc. does not alter
Abstract
Understanding bird migration and dispersal is important to inform full life-cycle conservation
planning. Stable hydrogen isotope ratios from feathers (δ2Hf) can be linked to amountweighted long-term, growing season precipitation δ2H (δ2Hp) surfaces to create δ2Hf isoscapes for assignment to molt origin. However, transfer functions linking δ2Hp with δ2Hf are
influenced by physiological and environmental processes. A better understanding of the
causes and consequences of variation in δ2Hf values among individuals and species will
improve the predictive ability of geographic assignment tests. We tested for effects of species, land cover, forage substrate, nest substrate, diet composition, body mass, sex, and
phylogenetic relatedness on δ2Hf from individuals at least two years old of 21 songbird species captured during the same breeding season at a site in northeastern Alberta, Canada.
For four species, we also tested for a year × species interaction effect on δ2Hf. A model
including species as single predictor received the most support (AIC weight = 0.74) in
explaining variation in δ2Hf. A species-specific variance parameter was part of all bestranked models, suggesting variation in δ2Hf was not consistent among species. The second best-ranked model included a forage substrate × diet interaction term (AIC weight =
0.16). There was a significant year × species interaction effect on δ2Hf suggesting that
interspecific differences in δ2Hf can differ among years. Our results suggest that withinand among-year interspecific variation in δ2Hf is the most important source of variance typically not being explicitly quantified in geographic assignment tests using non-specific transfer functions to convert δ2Hp into δ2Hf. However, this source of variation is consistent with
the range of variation from the transfer functions most commonly being propagated in
assignment tests of geographic origins for passerines breeding in North America.
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Species-Specific Feather Hydrogen Isotope Ratios
our adherence to PLOS ONE policies on sharing
data and materials (as detailed online in our guide
for authors, http://www.PLOSone.org/static/
editorial.action#competing).
Introduction
Each year, billions of birds migrate between breeding and wintering areas [1]. Migration and dispersal movements have been difficult to quantify for most of these species. Yet, this information is
important to identify the spatial scale at which population dynamics are taking place and should
be considered in conservation planning (e.g. [2, 3]). Recent studies have highlighted the importance of quantifying the level of migratory connectivity and extent of natal dispersal, i.e. straightline distance moved by an individual from its natal area to its first breeding site, in full life-cycle
assessments [4–6]. High migratory connectivity implies that the majority of individuals in a breeding population use the same wintering areas, whereas low migratory connectivity suggests sparsely
distributed individuals from a breeding population across the species wintering grounds [7].
Intrinsic markers like naturally occurring stable isotopes of several elements can provide
important information on where birds grow their feathers and have the advantage of not
requiring individuals to be recaptured when assessing movement dynamics. Among stable isotopes that have been used in movement studies (i.e. C, N, H, O, and S; [8]), stable hydrogen isotope ratios (2H:1H; depicted as δ2H) are now the most commonly used marker [9]. Predictable
spatial variation resulting from amount-weighted, growing-season mean precipitation (δ2Hp)
worldwide is well documented [10]. The resulting patterns of spatial variation in δ2Hp (i.e. isoscapes) have been used in combination with δ2H from feathers (δ2Hf) to infer geographic origin of birds as the H in bird feathers is ultimately derived from environmental waters where
the feather was grown [11, 12]. In the Nearctic-Neotropical migration system, feathers that are
grown prior to fall migration (pre-basic molt; [13]) may provide information on natal or previous breeding origin in North America, whereas feathers that are grown prior to spring migration (pre-alternate molt) can be used to identify the wintering grounds of breeding individuals
[14–16]. However, before assigning birds to geographic origins, δ2Hp values need to be
adjusted to reflect the difference between local precipitation driving food webs (δ2Hp) and δ2Hf
(generally from regression models; hereafter “transfer functions”; [8]). Clark et al. [11] provided transfer functions for waterfowl and songbirds sampled in North America. More
recently, Hobson et al. [17] found that foraging and migratory strategies were an important
source of variation that influenced the transfer function applied to migratory songbirds. They
suggested that δ2Hf differences between ground and non-ground foragers may result from differences in ground-level evapotranspiration [17] or differences in trophic level [18].
While differences between groups of species in the transfer function between δ2Hf and δ2Hp
have been documented, what causes this interspecific variation is not as well understood. Analytical approaches have been developed to deal with this uncertainty in Bayesian assignment
tests to provide more accurate and less biased estimates of likely geographic origin [19]. However, a better understanding of variation in δ2Hf among species with the same geographic origin should help in assessing those factors contributing to variation we see among various
transfer functions. For example, evaporative processes in response to increased activity or
ambient conditions may lead to higher δ2H in tissues [20]. Thus, birds nesting in open areas
(e.g. unforested and forest canopy) could have higher δ2Hf values relative to species associated
with forest understory. Increased body water loss due to metabolic activity can result in
enriched heavy isotopes in the body water pool, in turn leading to higher δ2Hf values, and this
effect might be more important in smaller individuals/species [21, 22]. However, Betini et al.
[23] reported the opposite pattern, where body mass of nestling Tree Swallows (Trachycineta
bicolor) was positively correlated with δ2H from blood samples. Phylogenetically conserved life
history traits [24, 25] and, potentially, conserved biochemical pathways controlling H isotope
discrimination in tissues [26, 27] among closely related species suggest a potentially important
phylogenetic component of δ2Hf that could explain important interspecific variation. Inter-
PLOS ONE | DOI:10.1371/journal.pone.0163957 November 2, 2016
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Species-Specific Feather Hydrogen Isotope Ratios
annual variation in δ2Hf has been reported for a few songbird species [28, 29] and, all things
being equal, this variation should be consistent across species nesting in the same region but, to
our knowledge, no studies have tested this assumption by quantifying the species × year interaction effect on variation in δ2Hf of forest songbirds. Finally, different species may seek out different local microhabitats during the molt period and these might also account for differences
in δ2Hf from the same general area but little is known about habitat use during this typically
“secretive” period of the annual cycle (e.g. [30]).
In this study, we used tail feathers collected from different songbird species during the same
breeding season and geographic area (within a ca. 130 km radius) to test various hypotheses
that have been proposed to explain intraspecific and interspecific variation in δ2Hf. Specifically,
we used a model selection approach to compare the relative importance of species, land cover
type, forage substrate, nest substrate, diet composition, body mass, sex, and phylogenetic relatedness in explaining variation in δ2Hf among experienced breeders (after second-year; ASY) of
21 songbird species (7 families and 16 genera). We predicted that ground foragers and insectivores (i.e. species feeding almost exclusively on invertebrates during the breeding season)
would have higher δ2Hf compared to non-ground foragers and omnivores (i.e. species feeding
on seeds, fruits, and insects during the breeding season), respectively. Observed δ2Hf for
ground and non-ground foragers were used to validate predicted values from the transfer functions provided by Hobson et al. [17]. We also predicted that individuals nesting in open areas
would have higher δ2Hf than those nesting in forest understory. Finally, we predicted that
closely related species (i.e. within the same genera) would have more similar δ2Hf values than
less related individuals. There were no a priori expectations regarding the direction of the effect
(positive or negative) of body mass and sex (male or female having higher δ2Hf) on δ2Hf.
Females are more likely to experience breeding dispersal movements, i.e. straight-line distance
moved by an individual from a breeding territory to another in subsequent years, and over
larger distances than males [31]. Thus, we predicted that females would have similar mean
δ2Hf values than males, but larger variation, assuming no bias in direction of dispersal movements. For four of our most common species, we also tested for a year × species interaction
effect on δ2Hf to determine whether annual variations in δ2Hf are consistent among species.
Methods
Study area and feather samples
The study was conducted at bird banding stations in the Lesser Slave Lake Provincial Park
(Lesser Slave Lake Bird Observatory, LSLBO; 55°20' N, 114°40' W) and the lower Athabasca oil
sands region (Owl Moon Environmental Inc.; 56°43' N, 111°22' W) in northeastern Alberta,
Canada. The region is characterized by conifer (black spruce, Picea mariana; white spruce,
Picea glauca; jack pine, Pinus banksiana), deciduous (trembling aspen, Populus tremuloides),
and mixedwood stands typical of the western boreal forest. The banding stations in the oil
sands region are similarly forested, but also occur in riparian areas and reclaimed mine sites.
Breeding birds have been captured at banding stations as part of the Monitoring Avian Productivity and Survivorship (MAPS) program [32]. In 2013, 32 MAPS stations were monitored
in the oil sands region (Table 1). Each banding station operated from 8 to 14 mist nets (each
net was 12 m × 2.6 m) and captured birds passively (i.e. no attempts were made to attract the
birds). Starting at sunrise, birds were captured at each station for 6 hours every 10 days
throughout the breeding season (mid-June–mid-August 2013; periods 5–10; [32]). The same
year, LSLBO monitored 4 MAPS stations within a forested area of approximately 3 ha that bordered the eastern shore of Lesser Slave Lake (Table 1). In 2011, active netting was conducted
within ca. 1 km of the closest MAPS station where males of four species (Ovenbird; Seiurus
PLOS ONE | DOI:10.1371/journal.pone.0163957 November 2, 2016
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Species-Specific Feather Hydrogen Isotope Ratios
aurocapilla, Swainson's Thrush; Catharus ustulatus, American Redstart; Setophaga ruticilla,
and Yellow-rumped Warbler; Setophaga coronata) were attracted to mist nets using conspecific
song playback. Additional samples were also collected from these 4 MAPS stations. Two 3rd
rectrices were plucked from as many captured individuals as possible and individual body
mass was recorded at time of capture. All feathers were stored in paper envelopes at room
Table 1. Locations, habitat descriptions, mean δ2Hf (± SD), and number of feather samples (n) collected from 36 capture locations in northeastern Alberta, Canada.
Lat
Long
Habitat (100 m radius)a
Habitat (Station)
Wetland area (m2)
δ2Hfb (± SD)
n
1
56.981
-111.619
Broadleaf
Exposed Land
13750
-136 (± 23)
14
2c
57.006
-111.608
Coniferous
Exposed Land
5000
-159
1
3c
57.022
-111.637
Mixedwood
Exposed Land
7500
-147 (± 17)
32
4
57.169
-111.536
Wetland
Wetland-Shrub
13125
-155 (± 3)
2
5
57.044
-111.538
Mixedwood
Exposed Land
2500
-147 (± 15)
4
6
57.247
-111.595
Mixedwood
Wetland-Shrub
0
-146
1
7
55.616
-111.041
Coniferous
Broadleaf
8125
-130 (± 27)
4
8
57.169
-111.038
Wetland
Water
21875
-150 (± 3)
4
9
57.080
-111.689
Wetland
Shrub-Tall
21875
-136 (±13)
10
10
57.248
-111.735
Mixedwood
Water
20625
-138 (±14)
14
11
57.240
-111.735
Mixedwood
Coniferous
15625
-144 (± 4)
5
12
56.201
-110.893
Mixedwood
Coniferous
13750
-123 (± 26)
4
13
56.997
-111.554
Mixedwood
Broadleaf
0
-136
1
14
57.382
-111.885
Broadleaf
Wetland-Shrub
8750
-138 (± 8)
5
15
57.393
-111.983
Mixedwood
Broadleaf
11250
-143 (± 4)
7
16
56.419
-111.375
Broadleaf
Wetland-Treed
5625
-149 (± 4)
2
17
56.697
-111.398
Broadleaf
Coniferous
9375
-140
1
18
57.301
-111.217
Mixedwood
Broadleaf
15000
-142 (± 11)
2
19
57.209
-111.692
Mixedwood
Broadleaf
23750
-145 (± 7)
4
20
55.536
-110.889
Broadleaf
Coniferous
10000
-136
1
21
57.313
-111.212
Coniferous
Broadleaf
10000
-144 (± 6)
4
22
57.181
-111.584
Broadleaf
Coniferous
625
-142
1
23
57.197
-111.046
Broadleaf
Wetland-Shrub
0
-137 (± 10)
6
24
56.916
-111.458
Broadleaf
Wetland-Shrub
11250
-150 (± 10)
12
25
56.924
-111.503
Coniferous
Broadleaf
1250
-149 (± 7)
5
26
57.155
-111.063
Broadleaf
Coniferous
0
-141 (± 4)
7
27c
57.040
-111.596
Broadleaf
Exposed Land
1250
-162 (± 10)
5
28
55.390
-110.744
Broadleaf
Coniferous
0
-138
1
29
55.571
-110.903
Broadleaf
Wetland-Treed
625
-124 (± 22)
2
30
56.190
-110.973
Broadleaf
Broadleaf
0
-141
1
31
57.198
-111.531
Broadleaf
Broadleaf
4375
-146 (± 3)
3
32
57.257
-111.041
Broadleaf
Coniferous
5000
-148 (± 7)
5
33d
55.429
-114.829
Coniferous
Wetland-Shrub
1250
-150 (± 9)
22
Station
Habitat information (i.e. dominant land cover type at point location [station] and within 100 m radius and wet area within a 100 m radius) was extracted from
the Earth Observation for the Sustainable Development of Forests EOSD [33].
Surrounding forest canopy dominated by: Broad Leaf = leafy deciduous vegetation, Coniferous = spruce, pine and needled vegetation, Mixed Wood = both
a
leafy and coniferous vegetation, and Wetland = tall vegetation limited in peat or grassy water dominated terrain.
b
c
d
Mean δ2Hf values for all feather samples collected at a given station.
Banding station within a reclaimed site.
Banding stations and mist netting sites from LSLBO were considered a single banding station (central location is provided) given they were all within a 1
km radius.
doi:10.1371/journal.pone.0163957.t001
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Species-Specific Feather Hydrogen Isotope Ratios
temperature. In the oil sands region, birds were captured and feathers were collected by KF, CG
(banders-in-charge), and their banding staff. At Slave Lake, birds were captured and feather samples were collected by RK (bander-in-charge), LSLBO banding staff, and volunteers.
Only feathers from males and females of at least two years old (i.e. after-second year individuals; ASY) were used for isotope analysis. These individuals were selected based on the higher site
fidelity reported in adult songbirds compared to first-year breeders [31, 34]. Also, adult Neotropical migratory passerines generally undergo complete pre-basic molts, including the replacement
of primaries and rectrices, at or near their breeding site [13]. Thus, for most species, our feather
samples should have reflected the isotopic signature incorporated at our study site in the previous
breeding season. Individuals from LSLBO were aged and sexed by the banders-in-charge, while
those from the oil sands region were aged and sexed by the banders-in-charge and photos were
reviewed by P. Pyle (Institute for Bird Populations; http://www.birdpop.org/). We further determined age of some S. aurocapilla by quantifying the wear pattern of the 3rd rectrices [35]. Feather
samples were required from a minimum of nine individuals for a species to be considered. For
each location, we also identified the dominant land cover type at the point level and in a 100 m
radius (exposed land, wetland-shrub, wetland-treed, shrub-tall, broadleaf, coniferous and water),
and wet area (ha) within a 100 m radius using the Earth Observation for Sustainable Development of Forests (EOSD; [33]). For each species, we assigned dietary categories (i.e. insectivore vs.
omnivore), forage substrate (i.e. upper canopy, lower canopy/shrub, and ground), and nest substrate (i.e. agriculture, bogs, tree / shrub swamp, coniferous, deciduous, early successional, marsh,
mixedwood, and open stands) using the Avian Life History Information Database (hereafter
“ALHD”; http://www.on.ec.gc.ca/wildlife/wildspace/project.cfm;Table 2).
Fieldwork was conducted in accordance with the Canadian Council for Animal Care and
the permit for this study was approved by the University of Alberta Animal Care Committee
(permit # AUP00000100). Federal and provincial bird banding and feather collection permits
for this study were approved by the Canadian Wildlife Service and Alberta Environment and
Sustainable Resource Development, respectively.
Stable isotope analysis
Surface oils were removed from all feathers by using a 2:1 chloroform:methanol solution. The
central vane of each feather was weighed (350 ± 20 μg) and samples were secured in silver capsules. Isotopic analysis was conducted at the Colorado Plateau Stable Isotope Laboratory at the
Northern Arizona University for 2011 samples and the Stable Isotope Hydrology and Ecology
Laboratory of Environment Canada for 2013 samples. Samples were exposed to high temperature (1350°C) flash pyrolysis and the separated H2 pulses were used to measure δ2Hf by continuous-flow isotope-ratio mass spectrometry (CF-IRMS). For both laboratories, we used the
comparative equilibration approach with the same in-house keratin working standards (KHS
[–54.1‰], SPK [–121.6‰], CBS [–197‰]) to account for exchangeable hydrogen in keratins
where δ2H of nonexchangeable H was established [36]. Thus we are confident that isotope
results are comparable within measurement error between the two laboratories (see [8]).
Results were expressed for non-exchangeable H delta notation (δ2Hf) in units of per mil (‰)
and the analytical error, based on within-run replicates of keratin reference standards (n = 5
per run) was ±2‰. Results are reported relative to the Vienna Standard Mean Ocean Water—
Standard Light Antarctic Precipitation (VSMOW-SLAP) scale.
Statistical analyses
Linear mixed models were used to explore how δ2Hf values from individuals of the selected
species captured in 2013 were influenced by species, individual, and land cover factors (fixed
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Species-Specific Feather Hydrogen Isotope Ratios
Table 2. Number of feather samples (n) collected from 21 songbird species breeding in northern Alberta, Canada.
Scientific Name
Empidonax alnorum
Setophaga ruticilla
Cardellina canadensis
Common Name (4-letter code)
N
Forage Substratea
Dietb
Nesting Substrate
Alder Flycatcher (ALFL)
15
A
I
Treed/shrubby swamp
American Redstart (AMRE)
14
LCS
I
Deciduous Woodland
Canada Warbler (CAWA)
14
LCS
I
Deciduous Woodland
Clay-coloured Sparrow (CCSP)
15
G
O
Coniferous Woodland
Bombycilla cedrorum
Cedar Waxwing (CEDW)
12
A
I
Open Woodland
Spizella passerina
Chipping Sparrow (CHSP)
15
G
O
Open Woodland
Geothlypis trichas
Common Yellowthroat (COYE)
9
LCS
I
Marsh
Least Flycatcher (LEFL)
15
A
I
Deciduous Woodland
Spizella pallida
Empidonax minimus
Melospiza lincolnii
Setophaga magnolia
Geothlypis philadelphia
Setophaga coronata
Seiurus aurocapilla
Lincoln’s Sparrow (LISP)
12
G
O
Bogs
Magnolia Warbler (MAWA)
11
LCS
I
Mixed Woodland
Mourning Warbler (MOWA)
13
G
I
Open Woodland
Yellow-rumped Warbler (YRWA)
13
LCS
I
Coniferous Woodland
Ovenbird (OVEN)
11
G
I
Deciduous Woodland
Red-eyed Vireo (REVI)
15
UC
I
Deciduous Woodland
Savannah Sparrow (SAVS)
14
G
O
Agricultural
Song Sparrow (SOSP)
12
LCS
O
Early Successional
Catharus ustulatus
Swainson’s Thrush (SWTH)
14
G
O
Mixed Woodland
Oreothlypis peregrina
Tennessee Warbler (TEWA)
14
UC
I
Bogs
Tachycineta bicolor
Tree Swallow (TRES)
15
A
I
Treed/shrubby swamp
Zonotrichia albicollis
White-throated Sparrow (WTSP)
13
G
O
Early Successional
Setophaga petechia
Yellow Warbler (YEWA)
13
LCS
I
Early Successional
Vireo olivaceus
Passerculus sandwichensis
Melospiza melodia
Life history summary was provided by Avian Life History Information Database (http://www.on.ec.gc.ca/wildlife/wildspace/project.cfm).
a
Description of Forage substrate: A = aerial, G = ground, LCS = lower canopy / shrub, UC = upper canopy.
b
Description of diet types: I = Insectivore, O = Omnivore.
doi:10.1371/journal.pone.0163957.t002
effects) and phylogenetic relationships across species (random effects). A Multivariate Normal
distribution was specified for each model where fixed effects are part of the mean specification,
while random effects are part of the covariance structure. The response variable (yij) was δ2Hf
for individual i (i = 1. . .n) of species j (j = 1. . .s). We examined 15 different fixed effects as possible explanatory factors for δ2Hf and compared them to a (0) null (intercept only) model. The
fixed effects included species (1—species, 2—forage substrate [ALHD], 3—diet [ALHD], and 4
—nest substrate [ALHD]), banding station (5—land cover type at banding station [EOSD], 6—
dominant land cover type [EOSD], 7—wetland area in 100 m radius of each banding station
[EOSD], and 8—latitude), individual (9—linear and 10—quadratic individual mass, and 11—
sex), and interactive effects (12—forage substrate × diet, 13—forage substrate × land cover, 14
—nest substrate × diet, and 15—forage substrate × diet × nest substrate; Table 3). We used the
Akaike Information Criterion corrected for small sample sizes (AICc; [37]) to select the most
parsimonious model describing variation in δ2Hf among feather samples.
Residual variance (σ2) was included as a random effect in our 15 models and we divided
each model into two subsets where variance in δ2Hf among species was estimated as homoscedastic (variation among species was assumed equal [σ2]; Hom1—Hom15) and heteroskedastic
(the assumption of variance equality among species was relaxed [σ2j]; Het1 -Het15). To examine the phylogenetic correlation in δ2Hf, we estimated a multiplier of the off-diagonal elements
in the Multivariate Normal covariance matrix defined as λ [38, 39]. A value of λ = 0 indicated
evolution of traits independent of phylogeny, while value of λ = 1 indicated traits evolving
according to Brownian motion. Values <1 indicated that phylogeny effect was weaker than
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Species-Specific Feather Hydrogen Isotope Ratios
Table 3. Candidate models considered in this study.
Model
Fixed Effectsa
Set-Hom
Set-Het
0
Null Model
σ2, λ
σ2j, λ
-
1
Species
σ2, λ
σ2j, λ
Species
2
ForSub
σ2, λ
σ2j, λ
Species
2
Scale
3
Diet
σ ,λ
σ2j, λ
Species
4
NestSub
σ2, λ
σ2j, λ
Species
5
LandStation
σ2, λ
σ2j, λ
Station
6
Land100m
σ2, λ
σ2j, λ
Station
7
WetArea
σ2, λ
σ2j, λ
Station
8
Latitude
σ2, λ
σ2j, λ
Station
9
IndMass
σ2, λ
σ2j, λ
Individual
10
IndMass2
σ2, λ
σ2j, λ
Individual
2
11
Sex
σ ,λ
σ2j, λ
Individual
12
ForSub × Diet
σ2, λ
σ2j, λ
Species
13
ForSub × Habitat
σ2, λ
σ2j, λ
Species
14
NestSub × Diet
σ2, λ
σ2j, λ
Species
15
ForSub × Diet × NestSub
σ2, λ
σ2j, λ
Species
For each model subset, the variance was estimated as homoscedastic, where δ2Hf variances are constant across all species (Set-Hom; σ2) or
heteroscedastic, where δ2Hf variances are flexible across all species (Set-Het; σ2j). All candidate models estimated strength of the phylogenetic correlation
(λ [38]). Each model also described processes acting at different levels (i.e. Individual, Species or Station).
a
Description of variables: ForSub = ground vs non-ground foragers, Diet = insectivore vs omnivore, NestSub = typical nesting habitat, LandStation,
Land100m and WetArea = land cover at station, dominant land cover within 100 m radius, and wetland are within 100 m according to EOSD [33],
respectively, IndMass and IndMass2 = linear and quadratic individual mass at time of capture, respectively.
doi:10.1371/journal.pone.0163957.t003
expected under the Brownian model. The covariance between two observations (yij, yik) and
corresponding Mutivariate Normal means (μij, μik) was defined as cov(yij, yij) = σj σk tjk λ,
where tjk is proportional to the shared evolutionary path length between species j and k.
Shared evolutionary path lengths were estimated using 5000 pseudo-posterior trees based
on genetic data [40]. A phylogenetic correlation matrix [41] was constructed for each of the
5000 trees. Elements of the correlation matrix were defined as lengths of branches shared
between species based on mean node heights [42, 43]. The different number of observations
per species meant we could not apply existing phylogenetic mixed model software which uses
only 1 observation per species. Therefore, we implemented a maximum likelihood estimating
procedure for Multivariate Normal mixed models using Markov-chain Monte Carlo methods
and a data cloning algorithm [44] using the ‘dclone’ R package [45] and JAGS [46].
A two-way ANOVA was used to test for a Year (2011 and 2013) × Species (Ovenbird, Swainson's Thrush, American Redstart and Yellow-rumped Warbler) interaction effect on δ2Hf. All
analyses were conducted using R version 3.1.0 [47]. Results are presented as mean δ2Hf ± standard deviation (SD) unless specified otherwise. We also extracted δ2Hp values for our study area
from the isoscape provided by Bowen et al. [48] (see also IsoMap, isomap.org). Values were
expressed as the annual mean growing season (i.e. months where mean monthly temp > 0°C)
and used to estimate δ2Hf for omnivores and insectivores following Hobson et al. [17].
Results
We analyzed δ2Hf from 278 ASY individuals of 21 songbird species captured in 2013 (Table 2).
Mean values for most species (15 species) ranged from -127‰ (Swainson's Thrush) to -162‰
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Species-Specific Feather Hydrogen Isotope Ratios
Fig 1. Mean δ2Hf (± 95% confidence intervals) for 278 ASY individuals of 21 songbird species breeding in
northern Alberta, Canada, in 2013. The dashed black and grey horizontal lines indicate the standard deviation of
the residuals from Hobson et al. [17]’s δ2Hf transfer functions for ground (Ground) and non-ground foraging (Nonground) songbirds, respectively. The phylogenetic tree was derived from 5000 pseudo-posterior trees; shorter
branch lengths occur between species that are more closely related with each other. Also indicated are the sample
size for each species and the six species removed from further analyses because they were believed to have
molted their tail feathers on the wintering grounds or during migration.
doi:10.1371/journal.pone.0163957.g001
(Savannah Sparrow), while six species (Chipping Sparrow, Tree Swallow, Red-eyed Vireo,
Least Flycatcher, Cedar Waxwing, Alder Flycatcher) had higher mean δ2Hf (-97‰ to -51‰;
Fig 1). Combined with large variation around mean values for these six species, these results
suggested that rectrices from these individuals were grown on the wintering ground or during
migration. These results, at the exception of those for Cedar Waxwing, are consistent with previous accounts [13, 49] and these six species were removed from further analyses. The remaining samples included 192 ASYs (43 females and 149 males) from 15 species. We also report
δ2Hf for 113 ASY of the 4 species captured in 2011 (Fig 2).
Standard deviations were smallest for Mourning Warbler (± 4‰) and largest for Song Sparrow (± 22‰; Fig 1). The 95% confidence intervals for species-specific mean δ2Hf overlapped
with the predicted range of δ2Hf values from the transfer functions of Hobson et al. [16] for
ground and non-ground foragers in our study area (Fig 1). Mean values of ground foragers and
non-ground foragers (irrespective of species) were -143 ± 14‰ and -144 ± 15‰, respectively,
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Species-Specific Feather Hydrogen Isotope Ratios
Fig 2. Mean δ2Hf (± 95% confidence intervals) for 4 songbird species breeding in northern Alberta,
Canada, in 2011 and 2013. The black and grey horizontal lines indicate standard deviation of the residuals from
Hobson et al. [17]’s δ2Hf transfer functions for ground (Ground) and non-ground foraging (Non-ground) songbirds,
respectively. Sample size is indicated above each bar.
doi:10.1371/journal.pone.0163957.g002
both 95% confidence intervals overlap with the respective δ2Hf estimates from Hobson et al.
[17] for our study area. Males and females had similar mean and standard deviation in δ2Hf
(-143 ± 14‰ and -146 ± 11‰, respectively).
Models incorporating a species-specific variance parameter (heteroscedasticity) performed
better than the homoscedastic model subsets (S1 and S2 Tables). Our top model, included species as predictor (Het1; wAICc = 0.74). The second-best ranked model included a nest
substrate × diet interaction (Het14; ΔAICc = 3.02; wAICc = 0.16). The next two models including nest substrate x diet x forage substrate and nest substrate as a single effect received little
support (Het15 and Het4; ΔAICc > 5), but were the only other models with a wAICc > 0.001.
The four top-ranked models included only species-level predictors and provided little evidence
for an important effect of phylogeny (λ  0.29), land cover (wAICc < 0.001), or individual
(wAICc < 0.001) in explaining variation in δ2Hf (S1 and S2 Tables). Mean δ2Hf ranged from
-135 ± 16‰ (mixedwood) to -162 ± 6‰; (agriculture) across nest substrate (Fig 3) and was
-142 ± 17‰ and -145 ± 12‰ between omnivores and insectivores, respectively (Fig 3). Lastly,
there was a significant species × year interaction effect (F7, 157 = 19.9, p < 0.001). Three of the
four species had higher δ2Hf values in 2013 compared to 2011 (4‰, 9‰, and 12‰, respectively), while the Ovenbird had lower δ2Hf values in 2013 compared to 2011 (-6‰; Fig 2).
Discussion
This study demonstrates important interspecific differences in δ2Hf among songbird species
breeding in the same region. Species was the strongest predictor of the variation in δ2Hf among
individuals followed by a nesting substrate × diet composition interaction effect. Limited
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Species-Specific Feather Hydrogen Isotope Ratios
Fig 3. Mean δ2Hf (± 95% confidence intervals) for 15 songbird species grouped by diet and habitat
association. Individuals were captured in 2013 and assumed to have molted their feathers prior to fall migration
the previous year. Means values are reported by diet and habitat association according to the Avian Life History
Information Database (http://www.on.ec.gc.ca/wildlife/wildspace/project.cfm). The black and grey horizontal lines
indicate standard deviation of the residuals from Hobson et al. [17]’s δ2Hf transfer functions for ground (Ground)
and non-ground foraging (Non-ground) songbirds, respectively. Also indicated is the number of samples for each
category and species in brackets.
doi:10.1371/journal.pone.0163957.g003
support was found for single effect models that included life history traits, individual (sex and
body mass), or land cover predictors. Some studies have found support for these predictors
[17, 23, 50], but they did not compare the relative importance of many predictors for different
levels of organization. We also showed that differences in δ2Hf between years are not always
consistent among species. Our results provide important insights regarding different sources of
error being propagated in Bayesian assignment tests and suggest that the use of species- and
year-specific δ2Hf isoscapes could improve the accuracy of assigned geographic origin of birds
(see also [51], but see [52]).
Based on results from Hobson et al. [17], we predicted that ground foraging songbirds
would have higher δ2Hf compared to those foraging in the upper- or lower-canopy. Mean δ2Hf
values or corresponding 95% confidence intervals for the 15 focal species did indeed overlap
with predicted values from the transfer functions of Hobson et al. [17] applied to our study
area. However, models with foraging substrate as a single predictor received very little support
(ΔAICc > 26.6). There was also no evidence that songbirds using open habitat or forest canopy
during the nesting period had higher δ2Hf compared to those using forest understories. In temperate or boreal ecosystems, differences in ground temperature between closed and open habitats may not influence evapotranspiration rates and, ultimately, δ2Hf. For example, Hache et al.
[29] found no difference in δ2Hf between nestlings from recent selection harvesting (open) vs
unharvested stands (closed). However, most adult songbirds start molting during the postfledgling period and some mature forest specialists have been shown to aggregate in open-
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Species-Specific Feather Hydrogen Isotope Ratios
canopy clearcuts for concealment from predators during this period [30, 53]. Thus, many focal
species might have used similar microhabitat and experienced similar temperatures and sun
exposure during the molting period irrespective of their nesting substrate. Species-specific variation in timing and location of molt (e.g. [54]) could also result in important spatio-temporal
variation in δ2Hf of ASY songbirds from a given region, but it is unclear to what extent
resources consumed during the nesting period can be integrated in tissues that have grown
during the post-fledging period (e.g. [55, 56]).
Birds with larger body sizes could have lower δ2Hf than smaller birds because larger individuals or species lose proportionately less of their total body water to evaporative processes [21,
22]. However, there was no evidence in our study to suggest body size was important for δ2Hf
in adult songbirds, but differences in body mass among individuals at the time of capture
might not reflect differences during the molting period. Females also did not have different
δ2Hf values than males [57] and variation around mean δ2Hf was only slightly lower for males
than females. These results indicate that population level assignments can be generated irrespective of body size and sex of individuals.
Breeding dispersal distances appear to be species-specific [57, 58] and would often occur over
relatively short distances. Variation in mean δ2Hf can be used as a proxy for breeding dispersal
rate and distance, i.e. species with larger variation might have a higher proportion of individuals
that experienced breeding dispersal movements and/or dispersed over larger spatial extents. The
relatively small variation around mean δ2Hf reported for all focal species in this study suggests
that most dispersal events would have occurred within the isocline corresponding to predicted
δ2Hf for our study area. However, differences in mean δ2Hf among species could also reflect population-level post-breeding movements (i.e. within year dispersal movements prior to fall migration) and molt occurring elsewhere in the species breeding range (e.g. [59]).
The better performance of heteroscedastic compared to homoscedastic variance models
suggests an important species-specific component for future songbird assignment of geographic origins using δ2Hf. Differences in variation around species-specific mean δ2Hf in a
region might reflect interspecific differences in breeding dispersal rates, but also differences in
niche breath. Habitat generalists use a broader range of land cover types which could result in
greater variation in δ2Hf than habitat specialists. However, species-specific tolerance (i.e. the
range of environmental conditions over which a species occurs; [60]) was not a good predictor
of variation in δ2Hf for 13 of our focal species (R2 = 0.05; p = 0.46; S1 File). However, the interspecific variation in the range of environmental conditions used by forest songbirds might not
be correlated with the range of δ2Hp values encountered by these species.
Studies have shown morphological traits to be more similar in closely related passerine species while for other traits, such as behavior and habitat associations, this might not be the case
[24]. In this study, closely related species did not have more similar δ2Hf values than less
related species. Our 15 focal species represented only 3 families (i.e. Passeridae, Parulidae, and
Turdidae) and may have been too closely related to detect phylogenetic effects. We also
expected a consistent difference in δ2Hf between years (2011 vs 2013) for the 4 focal species,
but this effect was not observed. If year effects on δ2Hf were exclusively driven by differences in
δ2Hp across years, we would expect a proportionate year effect across species breeding in the
same region. Future studies should aim to identify the underlying mechanisms explaining this
interaction effect. This could potentially be achieved by quantifying differences in δ2Hf for a
broader range of species and years. Nonetheless, along with species-specific variation in δ2Hf,
this species × year interaction effect was another important factor and likely corresponds to a
large proportion of the variance being propagated in Bayesian assignment tests [52].
We provided evidence suggesting that the most important source of error being propagated
in assignment tests of geographic origin of birds is likely interspecific variation in δ2Hf.
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Species-Specific Feather Hydrogen Isotope Ratios
However, we had limited success identifying the underlying mechanisms. Future studies should
determine whether missing variables or interaction terms could explain interspecific variation
in δ2Hf or more precisely determine where birds undergo the prebasic molt relative to breeding
territories. A better understanding of the variation in δ2Hf within and across years (i.e. across a
larger number of species and years) should provide important information about sources of
error being propagated in assignments of geographic origin. Transfer functions to explicitly
account for these sources of error would likely help generate more precise and accurate assignments and provide better information on migratory bird movements to inform full-cycle conservation strategies. However, our ability to integrate these sources of variance in assignment
tests will depend on the objectives. For example, it might be unrealistic to expect that speciesand year-specific δ2Hf isoscapes would be available over large spatial extent. Alternatively, it
would be possible to document regional dispersal movements [3, 4]. Results from Vander Zanden et al. [52] also suggest that the need to use year-specific δ2Hf isoscapes would depend on
the study region because the degree of inter-annual variation in δ2Hp differs among regions. It
is also likely that we are close to identifying the limit of accuracy of this single isotope
approach, highlighting the importance of combining multiple markers in multivariate assignment tests [59, 61–63].
Finally, there are a number of caveats that need to be considered in our study and future
research is encouraged to investigate further potential mechanisms contributing to within-site
variance in δ2Hf values. For example, it is still unclear how local hydrology interacts with biology by influencing relationships between δ2H values of foodwebs used by birds during the molt
period and their subsequent δ2Hf values. At interior continental sites, there are extreme seasonal effects in precipitation δ2H values [64] and northern sites will also have potential contributions from snowmelt as well as growing-season precipitation. These factors can strongly
influence resulting assumed environmental δ2H values experienced by molting birds. In northern regions where H from snowmelt contributes to the overall foodweb leading to bird feathers,
the use of an amount-weighted mean annual precipitation δ2H value or an average corresponding to those months where δ2H from precipitation has the strongest influence on the foodweb
may be more appropriate. Nonetheless, our study provides encouraging evidence that once isotopic variance is understood and accounted for, current assignment isotopic models provide a
valuable means of propagating such variance into the most parsimonious depiction of origins
for North American passerines.
Supporting Information
S1 File. Relationship between niche breadth and δ2Hf variation.
(DOCX)
S1 Table. Candidate models ranked according to AICc weights (wAICc).
(DOCX)
S2 Table. Parameter estimates from the top-ranked model used to explain variation in δ2Hf
among 192 adult migratory songbirds (Het1).
(DOCX)
Acknowledgments
We are grateful to N. Waters and E. Chidambara-vasi for assisting in lab work and to Alberta
Parks, Lesser Slave Lake Bird Observatory, and the C/N Elemental Analysis Laboratory (University of Alberta) for logistic support.
PLOS ONE | DOI:10.1371/journal.pone.0163957 November 2, 2016
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Species-Specific Feather Hydrogen Isotope Ratios
Author Contributions
Formal analysis: PS SH CJN EMB KAH.
Methodology: CJN SH EMB KRF CMG RK PP KAH.
Project administration: SH.
Writing – original draft: CJN SH EMB KAH PS KRF CMG PP.
Writing – review & editing: CJN SH EMB KAH PS KRF CMG PP.
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